Accurate gene expression profiling Facing the issues of normalisation and efficiency. Tania Nolan

Transcription

1 Accurate gene expression profiling Facing the issues of normalisation and efficiency Tania Nolan 1

2 Variations in RNA extraction Cultured cells Tissue section Selected Cells Total RNA extraction by column Total RNA extraction by Guanidinium reagent mrna purification AAAAAAAAAAAA AAAAAAAAAAAA 2

3 Total RNA AAAAAAAAAAAA One tube assay AAAAAAAAAAAA Two tube assay mrna target-specific primers Tth polymerase or RTase + Taq pol RT priming oligo-dt or random primers or random primers and oligo -dt or target-specific primers Reverse Transcriptase QPCR Target-specific PCR primers Taq polymerase 3

4 Favourite QRT-PCR Priming strategies All onto total RNA % of response random primers oligo dt random primers + oligo dt specific priming 4 Data from participants of yahoo groups; qpcrlistserver Bustin, Benes, Nolan, Pfaffl (2005) JME in press

5 Total RNA AAAAAAAAAAAA Two tube assay oligo-dt or random primers RT priming Reverse Transcriptase Target-specific PCR primers and fluorescent probe QPCR Taq polymerase 5

6 Random primed RNA (2x) dilution series (QPCR NHE1)

7 7 Random primed RNA (2x) dilution series (QPCR NHE1)

8 8 Random Priming RT and QPCR (100 fold dilutions, ß-actin) is reproducibly none linear

9 Gene quantification is not reproducible between different RT reactions 10 GAPDH 10 βactin NHE

10 10 Gene specific priming RT and QPCR (10 fold dilutions, GAPDH)

11 From RNA to cdna to gene expression data o Random priming of total RNA dilutions did not give a linear response Random primed RT reactions appear to be reproducibly none linear from reaction to reaction when run together o Random primed RT reactions do not appear to be reproducible from reaction to reaction when run on different occasions Specific priming of RNA dilutions appeared to give a linear response 11

12 From RNA to cdna to gene expression data Further Study: Investigate different RT priming strategies Investigate priming total RNA and mrna Investigate the effects of these variables on data interpretation Investigate effect of template structure on RT- QPCR sensitivity and efficiency 12

13 Comparing RT Priming Strategies GAPDH Constant RNA input concentration 35 Specific total RNA random total RNA oligo total 35 Specific mrna random mrna oligo mrna r+o total C t 25 C t Colorectal cancer sample Colorectal cancer sample 13

14 Sensitivity and efficiency using mrna GAPDH random+odt y = x R2 = oligo-dt y = x R 2 = random y = x R2 = % sensitivity rel to specific priming specific y = x R2 = % amplification efficiency random oligo-dt ran+odt priming method 14 GAPDH - mrna serial dilution 50 specific random oligo-dt ran+odt priming method

15 From RNA to cdna to gene expression data - GAPDH GAPDH Comparisons: Using total or mrna specific priming appears most sensitive When priming strategies are compared using mrna serial dilutions specific priming appears most sensitive and results in highest amplification efficiency 15

16 Total RNA vs mrna - IGF-I 40 specific total specific mrna random total random mrna C t C t Colorectal cancer sample Colorectal cancer sample 16 C t oligo-dt total oligo-dt mrna Colorectal cancer sample

17 Sensitivity and efficiency using mrna IGF Ct rand and dt specific random oligo dt Log input RNA concentration 17

18 Sensitivity and efficiency using mrna IGF y = x R 2 = y = x R 2 = y = x R 2 = rand and dt random oligo dt Linear (oligo dt) Linear (rand and dt) Linear (random)

19 From RNA to cdna to gene expression data IGF1 IGF1 Comparisons: All priming strategies relatively insensitive Using total or mrna Oligo dt priming appears most sensitive When priming strategies are compared using mrna serial dilutions Oligo-dT or random priming appear most sensitive and results in highest amplification efficiency Specific priming is very poor (slight improvement on mrna) 19

20 Data interpretation GAPDH Total RNA Specific Random hexamers Oligo (dt)15 Mixed 10 5 Samples GAPDH mrna Specific Random hexamers Oligo (dt) Samples

21 IGF-I Total RNA Specific Random hexamers Oligo (dt)15 Mixed 10 1 Samples IGF-I mrna Specific Random hexamers Oligo (dt) Samples

22 IGF-I/GAPDH total RNA Specific Random hexamers Oligo (dt)15 Mixed Samples IGF-I/GAPDH mrna Specific Random hexamers Oligo (dt) Samples

23 Influence of priming strategy on data interpretation Using constant input total or mrna Interpretation of normalised data using random or oligo dt priming results in similar interpretation Specific priming results in great variation (due to IGF1 priming) mrna appears to predict lower relative quantities than total RNA (by around 100 fold) 23

24 IGF1 structure 37ºC 60ºC 24

25 Comparing priming: IL y = x R 2 = One tube assay (RNA dilutions) - Specific primers Slope = y = x R 2 = Two tube assay (cdna dilutions) - Random primers Slope =

26 26 IL-15

27 37ºC IL-15 60ºC Reverse primer Reverse primer 27

28 Influence of target structure on priming efficiency Using total RNA or cdna dilution series Random priming appears to be more forgiving of secondary structure Specific primers need to be located within open regions (at 60 C or RT temperature) 28

29 37ºC GAPDH 60ºC 29

30 GAPDH 5 37ºC 60ºC 30 8 unpaired bases 12 unpaired bases

31 GAPDH Centre 1M NaCl ºC 60ºC 5 unpaired bases 10 unpaired bases

32 37ºC GAPDH 3 60ºC unpaired bases 24 unpaired bases

33 Total RNA target GAPDH specific primed dilution series y = x R 2 = y = x R 2 = y = x R 2 = FAM 5 Hex Centre Cy5 3 Linear (FAM) Linear (Hex) Linear (Cy5) 33 Assays designed by Natalie Simpson at

34 QRT-PCR protocol considerations When possible quantify input RNA Include a constant RNA amount into each RT Correct for RT batch to batch variations (Placenta 26 (2005) 93-98) 34

35 QRT-PCR protocol considerations For unknown amounts of RNA: Design specific reverse primers to open regions of transcript (at RT temperature) [ Use specific primers to increase sensitivity (especially when a large difference in transcript quantities is expected) Or use mrna since all priming strategies appear to give limited linear response Whichever system is chosen check linearity and dynamic range of priming strategy for all genes to be measured. 35

36 Many Thanks to: Prof Stephen Bustin (QMUL, London, UK) Dr Reinhold Mueller and Gothami Padmabandu (Stratagene, La Jolla, USA) Dr Helen Lacey and Prof Colin Sibley (Manchester University Medical School, UK) Natalie Simpson (Sigma-Genosys, Cambridge, UK) 36